Neural network identification and characterization of digital satellite channels: Application to fault-detection
The paper proposes a neural network technique to adaptively model and characterize digital satellite channels. The neural network model allows to identify each component of the channel by the use of the channel input-output signals as learning data. This technique was applied to fault detection in digital satellite links, especially those arising in on-board devices. The paper gives simulation examples of changes in the on-board filter characteristics. Our adaptive method allows to determine the origins of the changes and gives the new characteristics of the channel.
|Conference||Proceedings of the 1997 IEEE International Conference on Communications, ICC. Part 3 (of 3)|
Ibnkahla, M, Sombrin, J., & Castanie, F. (1997). Neural network identification and characterization of digital satellite channels: Application to fault-detection. In IEEE International Conference on Communications (pp. 1231–1235).